Gasgoo Munich- EBKernel has recently closed a new financing round worth 100 million yuan. The round was led by top industrial investors with deep roots in neuromorphic and embodied intelligence, with participation from existing shareholders and leading funds. Multi-Dimensional Capital acted as the exclusive financial advisor. Meanwhile, a subsequent funding round is currently in the final stages of closing.
The company plans to channel the capital into core technology R&D, team expansion, and global market growth. The focus is on accelerating the development, engineering implementation, and real-world validation of its Cognitive World Model.
EBKernel was founded by Zhu Senhua, who serves as CEO. A veteran in AI and brain cognition research, Zhu previously served as Director of the Huawei Cloud AI Algorithm Innovation Lab. There, he spearheaded company-level initiatives including the AI Brain Science Cloud Platform, the Pangu Embodied Large Model, and the Global Embodied AI Industry Innovation Center.
Co-founder Liu Jinyu brings extensive experience in technical productization and commercialization within the AI and robotics sectors. He has led the zero-to-one incubation and global commercialization of multiple product divisions, accumulating deep expertise in product incubation, market expansion, and scaled delivery across industrial and commercial scenarios.
The core team hails from leading research institutions such as Tsinghua University, Peking University, Fudan University, and the Chinese Academy of Sciences. Many previously worked at industry giants like Huawei, Lenovo, Megvii, and Geek+, contributing to AI algorithms, robotics systems, supply chains, and global commercialization. This background ensures Juna Panshi’s capabilities span the entire value chain—from technical roadmapping and systems engineering to customer scenarios and industrial delivery—rather than remaining limited to frontier research.
Image Source: EBKernel
Specifically, EBKernel adopts neuromorphic intelligence as its underlying paradigm, aiming to build a Cognitive World Model for the physical world. Unlike models that merely predict changes, this system enables robots to autonomously set goals and execute tasks based on environmental cognition, while continuously learning from real-world feedback.
To achieve this, the company translates brain science principles—such as attention, memory, sparse computing, and active inference—into engineering-ready algorithm models and system architectures. The approach targets four core objectives: low data dependency, high generalization, lifelong learning, and low power consumption. These directly address the real-world constraints of data costs, cross-scenario adaptability, continuous operation, and computing power limitations in embodied AI deployment.
EBKernel has already completed multiple system-level technical verifications in areas such as embodied perception, interaction, planning, navigation, manipulation, and swarm intelligence. The company has advanced its Cognitive World Model from an algorithmic framework to actual robotic systems. It is collaborating with several upstream and downstream partners in China's automotive supply chain, and has also completed a proof-of-concept (PoC) in an industrial scenario in Japan alongside a local partner.
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